# Copyright (c) 2024 Intel Corporation
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#      http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from tensorflow.keras import Sequential
from tensorflow.keras import layers
from tensorflow.keras.initializers import Constant


def SequentialModel(**kwargs):
    return Sequential(
        [
            layers.InputLayer(kwargs["input_shape"]),
            layers.Conv2D(10, 3, kernel_initializer=Constant(value=0)),
            layers.MaxPool2D((4, 4)),
            layers.Flatten(),
            layers.Dense(20, kernel_initializer=Constant(value=0)),
            layers.Dense(kwargs.get("classes", 10), kernel_initializer=Constant(value=0)),
        ]
    )


def SequentialModelNoInput(**kwargs):
    return Sequential(
        [
            layers.Conv2D(10, 3, kernel_initializer=Constant(value=0)),
            layers.MaxPool2D((4, 4)),
            layers.Flatten(),
            layers.Dense(20, kernel_initializer=Constant(value=0)),
            layers.Dense(kwargs.get("classes", 10), kernel_initializer=Constant(value=0)),
        ]
    )
